Date: 2018-08-01
R version: 3.5.0
Corresponding author: matthew.malishev@gmail.com

How much of the population does the sampling effort capture?

Overview

This document uses the schisto mesocosm 2016 data to explore cercariae production from snail hosts of different body sizes (diameter in mm and mass in mg) over a 14 week period under high and low N/P nutrient conditions. Host reproduction (egg masses) is also calculated.

 

Mesocosm1 data sheet

Snail size per tank

Shell diameter (mm) per tank

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
par(mfrow=c(1,1))
ylim <- round_any(max(meso1$Diameter),10,ceiling)
boxplot(Diameter~Tank, data=meso1,
        ylim=c(0,ylim),
        col = "light blue",
        notch = T,xlab="Tank",ylab="Diameter (mm)",
        main=paste0("Shell diameter (mm) over ",max(meso1$Week)," weeks")
)
abline(h=mean(meso1$Diameter),col="pink",lty=3)

with(meso1,t.test(Diameter,Tank)) # t.test
## 
##  Welch Two Sample t-test
## 
## data:  Diameter and Tank
## t = -292.62, df = 54631, p-value < 2.2e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -19.45781 -19.19889
## sample estimates:
## mean of x mean of y 
##  5.822942 25.151292

Snail diameter (mm) distribution

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
den <- density(meso1$Diameter)
xlim <- round_any(max(den$x),10,ceiling) 
ylim <- round_any(max(den$y),0.1,ceiling)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     xlab="Diameter (mm)",
     ylab="Density",
     main=paste0("Overall shell diameter (mm) over ",max(meso1$Week)," weeks"))
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC 
abline(v=mean(meso1$Diameter),col=col,lty=3,ylim=c(0,ylim)) # get mean

# un/infected diameter 
# Uninfected
den <- density(meso1_UU$Diameter)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     xlab="Diameter (mm)",
     ylab="Density",
     main=paste0("Shell diameter (mm) over ",max(meso1$Week)," weeks"))
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC 
abline(v=mean(meso1_UU$Diameter),col=col,lty=3,ylim=c(0,ylim)) # get mean
par(new=T)
# Infected 
den2 <- density(meso1_II$Diameter) 
plot(den2,
     col=adjustcolor(col2,alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     xlab="",
     ylab="",
     main="")
polygon(den2, col=adjustcolor(col2,alpha=0.5),border=col2) # fill AUC 
abline(v=mean(meso1_II$Diameter),col=col2,lty=3,ylim=c(0,ylim)) # get mean
par(family="mono")
legend("right",legend=c("Uninfected","Infected"),col=c(col,col2),
       bty="n",pch=20,pt.cex=1.5,cex=0.7,y.intersp = 0.5, xjust = 0.5,
       title="",title.adj = 0.3,
       # text.font=2,
       trace=T,inset=0.1)

##   xchar= 1.181 ; (yextra,ychar)= -0.004785 0.004785 
##   points2( 46.27 46.27 , 0.1 0.09522 , pch= 20 20 , ...)

Snail size over time (weeks)

Shell diameter (mm) over time (weeks)
~1000 eggs inoculated at 0,2,4,6 weeks

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE)) # plot stacked plots
ylim <- round_any(max(meso1$Diameter),10,ceiling)
boxplot(Diameter~Week, data=meso1,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col,
        notch = T,xlab="Week",ylab="Diameter (mm)",
        main=paste0("Shell diameter (mm) over ",max(meso1$Week)," weeks"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Diameter),col=col,lty=3)
par(new=T)
points(x=c(1,3,5,7),y=rep(ylim/2,4),pch="~",col="red")# add inoculation points
# un/infected
boxplot(Diameter~Week, data=meso1_UU,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col,
        notch = T,xlab="Week",ylab="Diameter (mm)",
        main=paste0("Shell diameter (mm) over ",max(meso1$Week)," weeks \n(uninfected snails)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1_UU$Diameter),col=col,lty=3)
par(new=T)
points(x=c(1,3,5,7),y=rep(ylim/2,4),pch="~",col="red")# add inoculation points

# infected
boxplot(Diameter~Week, data=meso1_II,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col2,
        notch = T,xlab="Week",ylab="Diameter (mm)",
        main=paste0("Shell diameter (mm) over ",max(meso1$Week)," weeks \n (infected snails)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1_II$Diameter),col=col,lty=3)
par(new=T)
points(x=c(1,3),y=rep(ylim/2,2),pch="~",col="red")# add inoculation points

Snail size over time (weeks) per tank

Snail size density over time for all tanks (total = 48) have been saved as ‘Size_per_tank_over_time.pdf’ in /Users/malishev/Documents/Emory/research/mesocosm

~1000 eggs inoculated at 0,2,4,6 weeks

#### size dist per tank over time ('Snail size over time (weeks)' but for each tank)
# Plot Tanks with large nutrients at the beginning versus tanks with lower nutrients
# Pick high and low nutrient tanks to compare

# Focus on diameter rather than biomass

# Eight replicates per size class and NP combo: six received schisto, two didn't. (Replication factor)
# Select tank #. Max 48   
tank <- 45
par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE)) # plot stacked plots
snail <- subset(meso1,subset=Tank==tank) # get tank level indiviudals

ggplot(snail, aes(x = Diameter, y = as.factor(Week), fill=..x..)) + # geom_density_ridges()
  # scale = overlap
  geom_density_ridges_gradient(scale = 5, size=0.2,color="black", rel_min_height = 0.01,panel_scaling=T,alpha=0.2) +
  geom_density_ridges(scale = 5, size=0.2,color="black", rel_min_height = 0.01,fill="white",alpha=0.2) +
  # geom_density_ridges(scale = 5, size=0.2,color="white", rel_min_height = 0.01,fill=col,alpha=0.5) +
  scale_fill_viridis(name = "Diameter", alpha=0.1, option = "magma",direction=-1) + # "magma", "inferno","plasma", "viridis", "cividis"
  xlim(c(0,25)) +
  labs(title = paste0("Snail diameter over ",max(meso1$Week)," weeks for tank ",tank)) +
  xlab("Snail diameter (mm)") +
  ylab("Week") +
  plot_it_gg("white")

Body mass (mg) over time (weeks)

(Soft tissue dry mass in mg = 0.0096 * Diameter[in mm]^3)
~1000 eggs inoculated at 0,2,4,6 weeks

Outer
Outlier

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE))# plot stacked plots
ylim <- round_any(max(meso1$Mass),100,ceiling)
boxplot(Mass~Week, data=meso1,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col,
        notch = T,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col,lty=3)
points(x=c(1,3,5,7),y=rep(ylim/3,4),pch="~",col="red")# add inoculation points

### uninfected ###
boxplot(Mass~Week, data=meso1_UU,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col,
        notch = T,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks \n(uninfected)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col,lty=3)
points(x=c(1,3,5,7),y=rep(ylim/3,4),pch="~",col="red")# add inoculation points
### infected ###
ylim <- round_any(max(meso1_II$Mass),100,ceiling)
boxplot(Mass~Week, data=meso1_II,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col2,
        notch = F,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks \n(infected)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col2,lty=3)
points(x=c(1,3),y=rep(ylim/1.2,2),pch="~",col="red")# add inoculation points

Without outlier

Outlier

outer <- meso1[which(meso1$Mass==max(meso1$Mass)),][,c("Mass","Cercariae")] # identify outlier
outer
##           Mass Cercariae
## 16895 1239.301         0
par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE))# plot stacked plots
ylim <- round_any(max(meso1$Mass),100,ceiling)
boxplot(Mass~Week, data=meso1,
        outline = F,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,60),
        col = col,
        notch = T,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks without outlier"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col,lty=3)
points(x=c(1,3,5,7),y=rep(ylim/3,4),pch="~",col="red")# add inoculation points

### uninfected ###
boxplot(Mass~Week, data=meso1_UU,outline=F,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,60),
        col = col,
        notch = T,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks  \n(uninfected)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col,lty=3)
points(x=c(1,3,5,7),y=rep(ylim/3,4),pch="~",col="red")# add inoculation points
### infected ###
ylim <- round_any(max(meso1_II$Mass),100,ceiling)
boxplot(Mass~Week, data=meso1_II,
        # xlim=c(0,max(meso1$Week)),
        ylim=c(0,ylim),
        col = col2,
        notch = F,xlab="Week",ylab="Dry body mass (mg)",
        main=paste0("Body mass (mg) over ",max(meso1$Week)," weeks  \n(infected)"),
        xaxs = "i", yaxs = "i"
)
abline(h=mean(meso1$Mass),col=col2,lty=3)
points(x=c(1,3),y=rep(ylim/1.2,2),pch="~",col="red")# add inoculation points

Snail size and number of cercariae produced

Point size by cercariae number

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
with(meso1,plot(Diameter,log(Cercariae),pch=20,
                col=adjustcolor(col,alpha=0.5),
                cex=cex_cer+0.5,
                ylab="Log number of cercariae released over 90 mins",xlab=" Diameter (mm)"
))
title("Number of cercarie for each snail length (mm)")
abline(v=mean(meso1$Diameter),lty=3,col=col)# mean diameter
points(outer,col="red",pch=20) # plot outlier

Linear log

# summary(with(meso1,lm(log(Cercariae)~Diameter))) # linear log

Snail mass and cercariae produced (mg)

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
with(meso1,plot(log(Mass),Cercariae,pch=20,
                col=adjustcolor(col,alpha=0.5),
                cex=cex_cer+0.5,
                # cex=1.5,
                ylab="Number of cercariae released over 90 mins",xlab="Log dry body mass (mg)"))
title("Number of cercariae for each log snail mass (mg)")
abline(v=log(mean(meso1$Mass)),lty=3,col=col)# mean diameter
outer <- meso1[which(meso1$Mass==max(meso1$Mass)),][,c("Mass","Cercariae")] # identify outlier
points(outer,col="red",pch=20) # plot outlier

Snail size per tank

Shell diameter (mm)
Select tank #. max 48

tank <- 2
par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE)) # plot stacked plots
snail <- subset(meso1,subset=Tank==tank) # get tank level indiviudals
diam_total <- 1 # set ylim either to max for tank or max across all tanks (16.8)
den <- density(snail$Diameter) # get diameter density
xlim <- round_any(max(den$x),10,ceiling)
ylim <- round_any(max(den$y),0.05,ceiling)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),ylim=c(0,ylim),
     xlab="",ylab="",main=""
)
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC
abline(v=mean(snail$Diameter),col=col,lty=3,ylim=c(0,ylim)) # get mean
title(main=paste0("Shell diameter (mm) distribution for tank #",tank),
      xlab="Shell diameter (mm)")
title(ylab="Density",line=3.5)

### uninfected ###
snail_UU <- subset(snail,subset=Cercariae==0)
den <- density(snail_UU$Diameter) # get diameter density
xlim <- round_any(max(den$x),10,ceiling)
ylim <- round_any(max(den$y),0.05,ceiling)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),ylim=c(0,ylim),
     xlab="",ylab="",main=""
)
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC
abline(v=mean(snail_UU$Diameter),col=col,lty=3,ylim=c(0,ylim)) # get mean
title(main=paste0("Uninfected snails in tank #",tank),
      xlab="Shell diameter (mm)")
title(ylab="Density",line=3.5)

### infected ###
snail_II <- subset(snail,subset=Cercariae>0)
if(length(snail_II$Tank)>0){
  den2 <- density(snail_II$Diameter) # get diameter density
  plot(den2,
       col=adjustcolor(col2,alpha=0.5),
       xlim=c(0,xlim),ylim=c(0,ylim),
       xlab="",ylab="",main=""
  )
  polygon(den2, col=adjustcolor(col2,alpha=0.5),border=col2) # fill AUC
  abline(v=mean(snail_II$Diameter),col=col2,lty=3,ylim=c(0,ylim)) # get mean
  title(main=paste0("Infected snails in tank #",tank),
        xlab="Shell diameter (mm)")
}else{
  plot(0,0,type="n");title(main=paste0("Infected snails in tank #",tank)); text(0,0.5,paste0("No cercariae \nin tank #",tank))
}

Cercariae production over time

Cercariae shed over 90 mins per week
~1000 eggs inoculated at 0,2,4,6 weeks
Snail abundance over time (weeks)

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
xlim <- max(meso1$Week) # uses total num of weeks
ylim <- round_any(max(meso1$Cercariae),100,ceiling)
with(meso1,plot(Cercariae~Week,
                col=adjustcolor(col,alpha=0.5),
                type="h",
                lwd=5,
                xlim=c(0,xlim),ylim=c(0,ylim),
                xlab="",ylab="",main=""
))
abline(h=mean(meso1$Cercariae),col=col,lty=3,ylim=c(0,ylim)) # get mean
title(main=paste0("Cercariae production over ",max(meso1$Week)," weeks"),
      xlab="Week")
title(ylab="Number of cercariae shed in 90 mins",line=3.5)

Tank cercariae production over time per tank

Select tank #. max 48

tank <- 9
par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
cer_total <- 0 # set ylim either to max for tank (1) or max across all tanks (6100)

snail <- subset(meso1,subset=Tank==tank) # get tank level individuals
snail <- subset(snail,subset=Cercariae>0) # get only cercariae
xlim <- max(meso1$Week) # uses total num of weeks
ylim <- round_any(max(snail$Cercariae),100,ceiling)
ifelse(cer_total==1,ylim <- round_any(max(meso1$Cercariae),100,ceiling),ylim <- round_any(max(snail$Cercariae),100,ceiling))
## [1] 400
par(mfrow=c(1,1))
if(length(snail$Cercariae)>0){
  with(snail,plot(Cercariae~Week,
                  col=adjustcolor(col,alpha=0.5),
                  type="h",
                  lwd=5,
                  xlim=c(0,xlim),ylim=c(0,ylim),
                  xlab="",ylab="",main=""
  ))
  abline(h=mean(snail$Cercariae),col=col,lty=3,ylim=c(0,ylim)) # get mean
  title(main=paste0("Cercariae production for tank ",tank," over ",max(meso1$Week)," weeks"),
        xlab="Week")
  title(ylab="Number of cercariae shed in 90 mins",line=3.5)
  par(new=T)
  points(x=c(0,2,4,6),y=rep(max(snail$Cercariae)/3,4),pch="~",cex=1.5,col="red")# add inoculation points
}else{print(paste0("No cercariae in tank #",tank))}

#####

############################################################################################################
############################################################################################################
############################################################################################################

Mesocosm 2 data sheet

Clean data

meso2$Schisto <- as.integer(as.factor(meso2$Schisto))-1# convert Y/N in Schisto col to 1/0
# convert size to integers
meso2$Size <- gsub("Intermediate","2Intermediate",meso2$Size)
meso2$Size <- gsub("Small","1Small",meso2$Size)
meso2$Size <- gsub("Large","3Large",meso2$Size)
meso2$Size <- as.integer(as.factor(meso2$Size))

### get snails with egg masses
#### First get presence of schisto
meso2_UU <-  subset(meso2,Schisto==0)
meso2_II <- subset(meso2,Schisto==1)

# get uninfected snails with egg masses
eggs_UU <- subset(meso2_UU,Eggs>0)
# get infected snails with egg masses
eggs_II <- subset(meso2_II,Eggs>0)

# get size classes
small <- subset(meso2,Size==1) #small
int <- subset(meso2,Size==2) #intermediate
large <- subset(meso2,Size==3) #large

# get NP conc
high <- subset(meso2,NP=="High") # high NP conc
low <- subset(meso2,NP=="Low") # low NP conc

Egg mass distribution

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
den <- density(meso2$Eggs[meso2$Eggs>0]) # get only snails with eggs
xlim <- round_any(max(den$x),50,ceiling)
ylim <- round_any(max(den$y),0.01,ceiling)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     xlab="Number of egg masses",
     ylab="Density",
     main=paste0("Distribution of number of egg masses over ",max(meso1$Week)," weeks"))
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC
abline(v=mean(meso2$Eggs),col=col,lty=3,ylim=c(0,ylim)) # get mean

N/P concentration v egg mass

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE)) # plot stacked plots
ylim=round_any(max(meso2$Eggs),10)
with(meso2,stripchart(Eggs~NP,
                      method="jitter", jitter=0.1,
                      pch=20,cex=2,
                      # cex=cex_diam,
                      col=adjustcolor(col,alpha=0.3),
                      vertical=T,
                      ylim=c(0,ylim),
                      group.names=c("High","Low"),
                      xlab="",ylab="",main="")
)
abline(h=mean(meso2$Eggs),col=col,lty=3)
title(main=paste0("Number of egg masses for high and low N/P levels over ",max(meso1$Week)," weeks"),
      xlab="N/P level")
title(ylab="Number of egg masses",line=3.5)

### uninfected ###
with(eggs_UU,stripchart(Eggs~NP,
                        method="jitter", jitter=0.1,
                        pch=20,cex=2,
                        col=adjustcolor(col,alpha=0.3),
                        vertical=T,
                        ylim=c(0,ylim),
                        group.names=c("High","Low"),
                        xlab="",ylab="",main="")
)
abline(h=mean(eggs_UU$Eggs),col=col,lty=3)
title(main=paste0("Uninfected snails"),
      xlab="N/P level")
title(ylab="Number of egg masses",line=3.5)

### infected ###
with(eggs_II,stripchart(Eggs~NP,
                        method="jitter", jitter=0.1,
                        pch=20,cex=2,
                        col=adjustcolor(col2,alpha=0.3),
                        vertical=T,
                        ylim=c(0,ylim),
                        group.names=c("High","Low"),
                        xlab="",ylab="",main="")
)
abline(h=mean(eggs_II$Eggs),col=col2,lty=3)
title(main=paste0("Infected snails"),
      xlab="N/P level")

Phyto and Peri Distribution

phyto = flourescence units
peri = flourescence per 2 weeks / 3.5 inch^2 tile (gross productivity biomass rate)

par(bty="n", las = 1)
par(mfrow=c(1,1))
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
den <- density(meso2$Phyto_F)
xlim <- round_any(max(den$x),10000,ceiling)
ylim <- round_any(max(den$y),0.0001,ceiling)
plot(den,
     col=adjustcolor(col,alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     xlab="",ylab="",main=""
)
polygon(den, col=adjustcolor(col,alpha=0.5),border=col) # fill AUC
abline(v=mean(meso2$Phyto_F),col=col,lty=3,ylim=c(0,ylim)) # get mean
par(new=T) # add periphyton concentration
den2 <- density(meso2$Peri_F)
plot(den2,
     col=adjustcolor(col2,alpha=0.5),
     xlim=c(0,xlim), # uses xy lims from phyto
     ylim=c(0,ylim),
     xlab="",ylab="",main=""
)
polygon(den2, col=adjustcolor(col2,alpha=0.5),border=col2) # fill AUC
abline(v=mean(meso2$Peri_F),col=col2,lty=3,ylim=c(0,ylim)) # get mean
title(main=paste0("Resource concentration over ",max(meso1$Week)," weeks"),
      xlab="Resource concentration")
title(ylab="Density",line=3.5)
par(family='mono')
legend("topright",legend=c("Phytoplankton","Periphyton"),title="Resource type",
       border="white",pch=19,ncol=1,bty="n",
       cex=0.75,
       xjust=0.5,yjust=0.5,x.intersp = 0.5,y.intersp = 0.5,
       col=c(col,col2)
)

Egg Mass over time v presence of schisto

~1000 eggs inoculated at 0,2,4,6 weeks

par(bty="n", las = 1)
#plot_it(0,"blue","YlOrRd",1,"HersheySans") # set col function params
layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE)) # plot stacked plots
par(mar=c(3.5,5,2,2))
meso2$Week <- as.integer(meso2$Week)
xlim <- max(meso2$Week)
ylim <- round_any(max(meso2$Eggs),10)
with(meso2,stripchart(Eggs~Week,
                      method="jitter", jitter=0.1,
                      pch=20,cex=2,
                      col=adjustcolor(col,alpha=0.5),
                      vertical=T,
                      xlim=c(0,xlim), ylim=c(0,ylim),
                      group.names=unique(meso2$Week),
                      xlab="Weeks",
                      ylab="Number of egg masses",
                      main=paste0("Number of egg masses over ",xlim," weeks")
))
abline(h=mean(meso2$Eggs),col=col,lty=3)
par(new=T)
points(x=c(0,2,4,6),y=rep(max(ylim)/3,4),pch="~",cex=1,col="red")# add inoculation points
axis(1,at=c(0,xlim),labels=c("0",""))# bookending axis tick marks

### uninfected ###
with(eggs_UU, stripchart(Eggs~Week,
                         method="jitter", jitter=0.1,
                         pch=20,cex=2,
                         col=adjustcolor(col,alpha=0.3),
                         vertical=T,
                         xlim=c(0,xlim),ylim=c(0,ylim),
                         group.names=unique(eggs_UU$Week),
                         xlab="Weeks",
                         ylab="Number of egg masses",
                         main="Uninfected")
)
par(new=T)
points(x=c(0,2,4,6),y=rep(max(ylim)/3,4),pch="~",cex=1,col="red")# add inoculation points
axis(1,at=c(0,xlim),labels=c("0","16"))# bookending axis tick marks

### infected ###
with(eggs_II, stripchart(Eggs~Week,
                         method="jitter", jitter=0.1,
                         pch=20,cex=2,
                         col=adjustcolor(col2,alpha=0.3),
                         vertical=T,
                         xlim=c(0,xlim),ylim=c(0,ylim),
                         group.names=unique(eggs_II$Week),
                         xlab="Weeks",
                         ylab="Number of egg masses",
                         main="Infected")
)
par(new=T)
points(x=c(0,2,4,6),y=rep(max(ylim)/3,4),pch="~",cex=1,col="red")# add inoculation points
axis(1,at=c(0,xlim),labels=c("0","16"))# bookending axis tick marks

### Size class vs peri
#~1000 eggs inoculated at 0,2,4,6 weeks

Size class vs Egg mass (with schisto)

par(bty="n", las = 1)
#### Egg masses > 0
den <- density(small$Eggs[small$Eggs>0])
den2 <- density(int$Eggs[int$Eggs>0])
den3 <- density(large$Eggs[large$Eggs>0])
xlim <- round_any(max(den2$x),100) #den2 xlim
ylim <- round_any(max(den2$y),0.01,ceiling) # den2 ylim

colvec <- c(4,6,9) # index for colfunc color palette in plot_it function
par(mfrow=c(1,1))
plot(den,
     col=adjustcolor(colfunc[colvec[1]],alpha=0.5),
     xlim=c(0,xlim),
     ylim=c(0,ylim),
     # type="h",# fills density
     xlab="Number of egg masses",
     ylab="Density",
     main="Number of egg masses for each snail size class"
)
lines(den2,col=adjustcolor(colfunc[colvec[2]])) # den2
lines(den3,col=adjustcolor(colfunc[colvec[3]])) # den3
# fill densities
polygon(den, col=adjustcolor(colfunc[colvec[1]],alpha=0.5),border=colfunc[colvec[1]]) # fill AUC
polygon(den2, col=adjustcolor(colfunc[colvec[2]],alpha=0.5),border=colfunc[colvec[2]]) # fill AUC
polygon(den3, col=adjustcolor(colfunc[colvec[3]],alpha=0.5),border=colfunc[colvec[3]]) # fill AUC
# means
abline(v=mean(small$Eggs),col=adjustcolor(colfunc[colvec[1]]),lty=3,ylim=c(0,ylim)) # get mean
abline(v=mean(int$Eggs),col=adjustcolor(colfunc[colvec[2]]),lty=3,ylim=c(0,ylim)) # get mean
abline(v=mean(large$Eggs),col=adjustcolor(colfunc[colvec[3]]),lty=3,ylim=c(0,ylim)) # get mean

par(family="mono")
legend("right",legend=c("Small","Intermediate","Large"),col=c(colfunc[colvec[1:3]]),
       bty="n",pch=20,pt.cex=1.5,cex=0.7,y.intersp = 0.5, xjust = 0.5,
       title="Snail size class",title.adj = 0.3,text.font=2,
       trace=T,inset=0.1)

##   xchar= 3.937 ; (yextra,ychar)= -0.001435 0.001435 
##   points2( 147.7 147.7 147.7 , 0.03072 0.02928 0.02785 , pch= 20 20 20 , ...)
### Uninfected
small_UU <- subset(small,Schisto==0)
int_UU <- subset(int,Schisto==0)
large_UU <- subset(large,Schisto==0)
### Infected
small_II <- subset(small,Schisto==1)
int_II <- subset(int,Schisto==1)
large_II <- subset(large,Schisto==1)

Egg Mass per Week

~1000 eggs inoculated at 0,2,4,6 weeks

par(bty="n", las = 1)
# set data to appropriate class
meso2$Eggs <- as.numeric(meso2$Eggs)
d <- meso2
ggplot(meso2, aes(x = Eggs, y = as.factor(Week), fill=..x..)) + # geom_density_ridges()
  # geom_density_ridges_gradient(scale = 2, size=0.25, rel_min_height = 0.01,panel_scaling=T) +# scale = overlap
  # scale_fill_viridis(name = "Eggs", alpha=0.5, option = "magma",direction=-1) + # "magma", "inferno","plasma", "viridis", "cividis"
  geom_density_ridges(scale = 3, size=0.2,color="black", rel_min_height = 0.01,fill=col,alpha=0.5) +
  labs(title = paste0("Number of egg masses per week ")) +
  xlab("Number of egg masses") +
  ylab("Week") +
  # theme_ridges(grid=F,center_axis_labels = T)
  plot_it_gg("white")

#### uninfected ####
par(bty="n", las = 1)
ggplot(meso2_UU, aes(x = Eggs, y = as.factor(Week), fill=..x..)) + # geom_density_ridges()
  # geom_density_ridges_gradient(scale = 2, size=0.25, rel_min_height = 0.01,panel_scaling=T) +# scale = overlap
  # scale_fill_viridis(name = "Eggs", alpha=0.5, option = "magma",direction=-1) + # "magma", "inferno","plasma", "viridis", "cividis"
  geom_density_ridges(scale = 3, size=0.2,color="black", rel_min_height = 0.01,fill=col,alpha=0.5) +
  labs(title = paste0("Number of egg masses per week for uninfected hosts")) +
  xlab("Number of egg masses") +
  ylab("Week") +
  # theme_ridges(grid=F,center_axis_labels = T)
  plot_it_gg("white")

#### infected ####
par(bty="n", las = 1)
ggplot(meso2_II, aes(x = Eggs, y = as.factor(Week), fill=..x..)) + # geom_density_ridges()
  # geom_density_ridges_gradient(scale = 2, size=0.25, rel_min_height = 0.01,panel_scaling=T) +# scale = overlap
  # scale_fill_viridis(name = "Eggs", alpha=0.5, option = "magma",direction=-1) + # "magma", "inferno","plasma", "viridis", "cividis"
  geom_density_ridges(scale = 3, size=0.2,color="black", rel_min_height = 0.01,fill=col2,alpha=0.5) +
  labs(title = paste0("Number of egg masses per week for infected hosts")) +
  xlab("Number of egg masses") +
  ylab("Week") +
  # theme_ridges(grid=F,center_axis_labels = T)
  plot_it_gg("white")

  1. ‘This Supplementary Material can be found at https://github.com/darwinanddavis/SchistoMesocosm’↩